Inductive Bias

Inductive bias refers to the set of assumptions a learning algorithm makes to predict outputs for inputs it has not encountered during training. Without these inherent biases, a model would have no basis to generalize from observed data to unseen data. Different algorithms have different inductive biases, making some better suited for specific types of problems than others.