Natural systems learn to predict by implicitly learning from repeated pairings of two or more stimuli and events. Associative learning refers to a group of theories of knowledge acquisition that is based on the predictive relationships between two or more items or events. In its most basic form associative learning is the claim that a second item, or event, becomes linked to a first item, or event, as a consequence of repeated pairings. Associative learning theories are intended to apply across a wide range of species, stimuli, and modalities and hence have the potential to provide an overarching and unifying framework for the predictive mind and its evolutionary origins. These learning theories moreover suggest that future-oriented behavior can arise from simple learning principles.