A particle filter is a recursive Bayesian estimation algorithm used for estimating the state of a system that evolves over time and is partially observed. It approximates the posterior distribution of the state space using a set of particles, which are updated and resampled as new observations are made, making it particularly useful for non-linear and non-Gaussian processes.