What is inductive bias in supervised learning models?

Inductive bias is the set of assumptions a model uses to generalize beyond training data.

Since infinite functions can fit finite data, models need assumptions to choose one hypothesis. This is called inductive bias. For example, linear regression assumes linear relationships, while decision trees assume hierarchical feature splits. Without inductive bias, learning from limited data would be impossible.