In statistical terms, a biased model has error in its estimate even with infinite data. This can happen if the model is too simple, for example if it classifies samples into two classes when there are really three, or if it uses a linear curve for a nonlinear relationship. That relates to the ethical or political version of "bias" if this error benefits some group over others. Though if it was just some basic model off the shelf, that bias could just as well benefit/penalize anyone.