The RANSAC (Random Sample Consensus) algorithm is an iterative method used for estimating parameters of a mathematical model from a set of observed data that contains outliers. It works by randomly selecting a subset of the data to fit the model and then determining the number of inliers within a predefined threshold, iteratively refining the model to maximize the inlier count.