The Vector Space Model (VSM) is a mathematical framework used in information retrieval and natural language processing. It represents documents and queries as vectors in a multi-dimensional space, where each dimension corresponds to a unique term from the document collection. This allows for the comparison of documents based on their content by calculating the similarity between their vector representations. In VSM, the similarity is often measured using techniques like cosine similarity, which quantifies how closely aligned two vectors are. This model is foundational for various applications, including search engines and recommendation systems, enabling efficient retrieval of relevant information based on user queries.