A new theoretical framework treats human languages as latent spaces engineered for efficient data compression. The research suggests linguistic structures act as lossy encoders for conceptual thought. This perspective shifts how developers approach tokenization and embedding alignment. It offers a mathematical basis for improving cross-lingual transfer in large language models.