@jpeg729 answered the first question in a detailed way.
So for your second question:
Imbalanced data could be a problem, because your model might get too few “signals” from the rare data samples and thus overfit to the majority class.
Also measuring the accuracy might be problematic, since it can be pretty high by just predicting the majority class (see accuracy paradox 24).
In the end your model might have an accurcy of 99% just by predicting one class.