BUG: pandas.DataFrame.where doesn't work when cond is of Pandas Dtype
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd

df = pd.DataFrame()
df["input_col"] = ["a", "b", "c"]
df["is_valid_row"] = pd.Series([1, 1, 0], dtype="Int64")
df["output_col"] = df[["input_col"]].where(df["is_valid_row"] == 1)  # AssertionError is thrown here
```

#### Problem description

The code snippet is simplified to show that when using pandas.DataFrame.where in combination with a Pandas Dtype (Int64) an AssertionError is raised.
Note that when df["input_col"] (= pandas.Series.where) or dtype="int64" (instead of "Int64") is used, the code behaves as expected.

This behaviour is broken since Pandas >= 1.1 (still an issue in 1.1.2).

#### Expected Output

output_col
a
b
NaN

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.8.2.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United States.1252
pandas           : 1.1.2
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 46.2.0
Cython           : None
pytest           : 6.0.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.3.3
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : 1.3.19
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>
