Association Rule Learning is a data mining technique used to discover interesting relationships between variables in large datasets. It helps identify patterns, such as which products are frequently bought together, making it valuable for businesses. For example, if customers who buy bread often also buy butter, this insight can inform marketing strategies and product placements. The core of Association Rule Learning involves generating rules that express these relationships, typically in the form of "If A, then B." These rules are evaluated based on metrics like support, confidence, and lift, which help determine their strength and relevance in the dataset.