Association Rule Learning is a powerful data mining technique used to uncover interesting relationships and patterns among items in large datasets. It operates on the principle of identifying strong rules that reveal how variables are associated with one another. Commonly applied in market basket analysis, it helps businesses understand customer purchasing behavior by determining which products are frequently bought together. The method employs measures such as support, confidence, and lift to evaluate the strength and significance of these associations. Overall, Association Rule Learning is essential for making informed decisions in various fields, including retail, e-commerce, and beyond.