Information gain helps in reducing overfitting by selecting the most relevant features for decision-making. By ranking features based on their information gain, we can identify the most important features that contribute the most to accurate predictions. This process helps in reducing the dimensionality of the dataset, which in turn reduces the risk of overfitting. A model with fewer features is less likely to fit the noise in the data and is more likely to generalize well to new, unseen data.