BUG: pd.DataFrame.add() does not broadcast across levels, when level is None
- [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.

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**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

# create dataframe
df1 = pd.DataFrame({'A': [0, 1, 2], 'B': [1, 2, 3]})
df1.columns.set_names('L1', inplace=True)
# create dataframe with multiindex in column
df2 = pd.DataFrame({('A', 'C'): [0, 0, 0], ('A', 'D'): [0, 0, 0]})
df2.columns.set_names(['L1', 'L2'], inplace=True)

# returns dataframe of nans
df1.add(df2)
# returns dataframe with valid values
df1.add(df2, level=0)

```

#### Problem description

In pandas 0.23.2 the behavior was correct where level=None was treated as level=0 and being broadcasted. However in  pandas 1.0.3, it appears as though a bug got introduced.

#### Expected Output

Out[1]: 
   A   
   C  D
0  0  0
1  1  1
2  2  2

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.14.13-1.el7.elrepo.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.4.0.post20200518
Cython           : 0.29.17
pytest           : 5.4.2
hypothesis       : None
sphinx           : 3.0.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
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       : None
numba            : 0.49.1

</details>
