Conditional Random Fields (CRFs) are a type of discriminative probabilistic model used for structured prediction, especially in sequence labeling tasks where context is important. They model the conditional probability of a label sequence given an observation sequence, capturing dependencies between labels using undirected graphical models, which allows them to consider the entire input sequence for each prediction.