Feature propagation is a technique used in machine learning and data analysis to iteratively spread information across a network or graph, enhancing the representation of data points by considering their neighbors. This approach is particularly useful in semi-supervised learning and graph-based algorithms, where labeled data is limited but relational structures can be leveraged to improve model accuracy.