TF-IDF
TF-IDF (term frequency–inverse document frequency) is a scoring method that weighs how often a term appears in a document against how rare that term is across the whole catalog, so common words count for less than distinctive ones.
Part of Search Relevance
A term that appears in nearly every product description — like "the" or "product" — contributes little to relevance, while a term that appears in only a few listings is a much stronger signal of a match. TF-IDF is the older, simpler precursor to BM25, which builds on the same idea but adds length normalization and diminishing returns for repeated terms.