What is information gain in decision trees?

Information gain is the reduction in entropy achieved by partitioning the data based on a feature. It is used to determine the best feature to split on at each node in the decision tree. A feature with the highest information gain is chosen for the split, as it provides the most significant reduction in uncertainty.