Model-based learning is a methodological approach or academic concept centered on the construction, refinement, and utilization of explicit or implicit models of systems, environments, or phenomena. This concept investigates how agents or learners acquire knowledge and make decisions by leveraging predictive or explanatory models, enabling capabilities such as planning, simulation, inference, and efficient adaptation. Its significance lies in facilitating deeper understanding, improved generalization, and enhanced decision-making by moving beyond direct stimulus-response associations towards internal representations of underlying structures and dynamics.