BUG: `fillna()` on multiple columns with a series
- [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
df = pd.DataFrame([{'Cat1': None, 'Cat2': 'mouse', 'Cat3': 'dog'},{'Cat1': 'cat', 'Cat2': 'mouse', 'Cat3': 'dog'},])

print('One column')
print(df['Cat1'].fillna(df['Cat3']))
print()

print('Two columns with one column')
print(df[['Cat1', 'Cat2']].fillna(df['Cat3']))
print()

print('Two columns with two columns')
print(df[['Cat1', 'Cat2']].fillna(df[['Cat3', 'Cat3']]))
```

Output:
```
One column
0    dog
1    cat
Name: Cat1, dtype: object

Two columns with one column
   Cat1   Cat2
0  None  mouse
1   cat  mouse

Two columns with two columns
  Cat1   Cat2
0  NaN  mouse
1  cat  mouse
```

#### Problem description

`fillna()` on multiple columns with a series doesn't work in the same way that it does on a single column. I also tried to use a dataframe thinking that perhaps it needed a matching number of columns, but that only filled the column with `NaN` instead of the correct value.

#### Expected Output

```
One column
0    dog
1    cat
Name: Cat1, dtype: object

Two columns with one column
   Cat1   Cat2
0  dog  mouse
1   cat  mouse

Two columns with two columns
  Cat1   Cat2
0  dog  mouse
1  cat  mouse
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.9.0-12-amd64
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.4
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.1.1.post20200529
Cython           : 0.29.19
pytest           : 5.4.2
hypothesis       : 5.16.0
sphinx           : 3.0.4
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.15.0
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : 0.6.2
lxml.etree       : 4.5.1
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pytest           : 5.4.2
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.17
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.9
numba            : 0.49.1


</details>
