ZeroR as performance baseline for binary classfication model?
Sure, ZeroR is a perfectly fine baseline. In this case I think it's better to call it a random baseline rather than a majority baseline, since it's just what it is.
To my knowledge this is the only basic baseline usable with any classification task. Other baselines would involve something more sophisticated based on the specific task. The standard way to have a more competitive baseline is to used a state of the art method for the task.
Btw the baseline or evaluation method doesn't depend on the learning algorithm, it doesn't matter if it's NB or any other classification method.