Word vectors are numerical representations of words that capture their meanings, syntactic roles, and relationships with other words. These representations allow algorithms to process human language efficiently by translating words into mathematical formats. An example is Word2Vec, which plots words in a continuous vector space, where distance between vectors reflects similarity in meaning. This approach helps in tasks like sentiment analysis, translation, and information retrieval.