BUG: NA does not propagate through mask and where/ raises AssertionError in 1.1.0rc
- [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.

- [ ] (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
>>> a = pd.DataFrame([{'col': 'a'}] * 3).convert_dtypes()
>>> a
  col
0   a
1   a
2   a
>>> tfna = pd.Series([True, False, pd.NA]).convert_dtypes()
>>> tfna
0     True
1    False
2     <NA>
dtype: boolean
>>> a.mask(tfna, 'b')
  col
0   b
1   a
2   b
>>> a.where(tfna, 'b')
  col
0   a
1   b
2   b

```

#### Problem description

When replacing values with `mask` or `where`, `pd.NA` values in a boolean series used for the `cond` input are always replaced. This means `pd.NA` gets treated as `False` by `where` but as `True` by `mask`.

#### Expected Output

I would expect that `pd.NA` values in `cond` would propagate to the output.

```python
>>> a.mask(tfna, 'b')
    col
0     b
1     a
2  <NA>
>>> a.where(tfna, 'b')
    col
0     a
1     b
2  <NA>

```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.5
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.2.0.post20200712
Cython           : None
pytest           : 5.4.3
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.15.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pytest           : 5.4.3
pyxlsb           : None
s3fs             : 0.4.2
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
