The model assumes that each email is a mixture of topics, and each word is attributable to one of the email's topics. For instance, an email may contain a mix of topics such as "product updates," "promotions," and "customer feedback." LDA works by sampling from a distribution of topics and words to determine the most likely topics present in each email.