Cosine similarity is a metric used to measure how similar two vectors are, regardless of their size. It calculates the cosine of the angle between the two vectors in a multi-dimensional space, resulting in a value between -1 and 1. A value of 1 indicates that the vectors are identical, while a value of 0 means they are orthogonal, or completely dissimilar. This concept is widely used in various fields, including natural language processing and information retrieval. For example, in text analysis, cosine similarity helps determine how closely related two documents are based on their content, making it easier to find relevant information.