diff --git a/doc/source/whatsnew/v1.0.0.rst b/doc/source/whatsnew/v1.0.0.rst
index a6ba7770dadcc..d5231e63b7e6e 100755
--- a/doc/source/whatsnew/v1.0.0.rst
+++ b/doc/source/whatsnew/v1.0.0.rst
@@ -912,6 +912,7 @@ Other
 - Bug in :meth:`Series.diff` where a boolean series would incorrectly raise a ``TypeError`` (:issue:`17294`)
 - :meth:`Series.append` will no longer raise a ``TypeError`` when passed a tuple of ``Series`` (:issue:`28410`)
 - Fix corrupted error message when calling ``pandas.libs._json.encode()`` on a 0d array (:issue:`18878`)
+- Bug in ``pd.core.util.hashing.hash_pandas_object`` where arrays containing tuples were incorrectly treated as non-hashable (:issue:`28969`)
 - Bug in :meth:`DataFrame.append` that raised ``IndexError`` when appending with empty list (:issue:`28769`)
 - Fix :class:`AbstractHolidayCalendar` to return correct results for
   years after 2030 (now goes up to 2200) (:issue:`27790`)
diff --git a/pandas/_libs/hashing.pyx b/pandas/_libs/hashing.pyx
index d735890f7d07e..5298d8c5ed34e 100644
--- a/pandas/_libs/hashing.pyx
+++ b/pandas/_libs/hashing.pyx
@@ -70,6 +70,12 @@ def hash_object_array(object[:] arr, object key, object encoding='utf8'):
             # null, stringify and encode
             data = <bytes>str(val).encode(encoding)
 
+        elif isinstance(val, tuple):
+            # GH#28969 we could have a tuple, but need to ensure that
+            #  the tuple entries are themselves hashable before converting
+            #  to str
+            hash(val)
+            data = <bytes>str(val).encode(encoding)
         else:
             raise TypeError(f"{val} of type {type(val)} is not a valid type "
                             "for hashing, must be string or null")
diff --git a/pandas/core/util/hashing.py b/pandas/core/util/hashing.py
index fa3582755a202..43655fa3ea913 100644
--- a/pandas/core/util/hashing.py
+++ b/pandas/core/util/hashing.py
@@ -85,11 +85,12 @@ def hash_pandas_object(
     if isinstance(obj, ABCMultiIndex):
         return Series(hash_tuples(obj, encoding, hash_key), dtype="uint64", copy=False)
 
-    if isinstance(obj, ABCIndexClass):
+    elif isinstance(obj, ABCIndexClass):
         h = hash_array(obj.values, encoding, hash_key, categorize).astype(
             "uint64", copy=False
         )
         h = Series(h, index=obj, dtype="uint64", copy=False)
+
     elif isinstance(obj, ABCSeries):
         h = hash_array(obj.values, encoding, hash_key, categorize).astype(
             "uint64", copy=False
diff --git a/pandas/tests/util/test_hashing.py b/pandas/tests/util/test_hashing.py
index ebbdbd6c29842..ee9c4ed12bd92 100644
--- a/pandas/tests/util/test_hashing.py
+++ b/pandas/tests/util/test_hashing.py
@@ -353,3 +353,24 @@ def test_hash_collisions():
 
     result = hash_array(np.asarray(hashes, dtype=object), "utf8")
     tm.assert_numpy_array_equal(result, np.concatenate([expected1, expected2], axis=0))
+
+
+def test_hash_with_tuple():
+    # GH#28969 array containing a tuple raises on call to arr.astype(str)
+    #  apparently a numpy bug github.com/numpy/numpy/issues/9441
+
+    df = pd.DataFrame({"data": [tuple("1"), tuple("2")]})
+    result = hash_pandas_object(df)
+    expected = pd.Series([10345501319357378243, 8331063931016360761], dtype=np.uint64)
+    tm.assert_series_equal(result, expected)
+
+    df2 = pd.DataFrame({"data": [tuple([1]), tuple([2])]})
+    result = hash_pandas_object(df2)
+    expected = pd.Series([9408946347443669104, 3278256261030523334], dtype=np.uint64)
+    tm.assert_series_equal(result, expected)
+
+    # require that the elements of such tuples are themselves hashable
+
+    df3 = pd.DataFrame({"data": [tuple([1, []]), tuple([2, {}])]})
+    with pytest.raises(TypeError, match="unhashable type: 'list'"):
+        hash_pandas_object(df3)