Should we use non-linear models for "linear" data?

So I had an argument with an interviewer who asked me why I didn't just use a non-linear classification model on the linearly separable data that I had in one of my projects that I described to him, even though I had no computational constraints. I told him that it was because, irrespective of computational cost, a linear model is always preferable if you have linear data because it is simpler and captures general pattern while non-linear models might overfit …

classification classification model computational constraints data datascience linear non-linear projects