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. A cosine similarity of 1 indicates that the vectors are identical, while a value of 0 means they are orthogonal, or completely dissimilar. This method is commonly used in various fields, including natural language processing and information retrieval, to compare documents or text. By transforming text into numerical vectors, cosine similarity helps identify how closely related different pieces of content are, aiding in tasks like recommendation systems and clustering.