Which of the following allows for the discovery and classification of data in DLP?

The option that correctly identifies the functionality for the discovery and classification of data in Data Loss Prevention (DLP) is the choice that emphasizes both aspects: "Discovery and Classification." This functionality is crucial as it enables organizations to identify sensitive data across their systems and effectively categorize it based on its importance and regulatory requirements.

Discovery involves scanning and identifying where data resides, whether on endpoints, servers, or in the cloud, allowing for a thorough understanding of an organization’s data landscape. Classification follows, where the identified data is labeled according to its sensitivity level, which can vary from public to highly confidential information. This step is vital for any DLP strategy since it empowers organizations to implement the appropriate security measures based on the classification of the data, ensuring compliance and risk management.

The other choices, while they relate to DLP and security processes, do not specifically cover the entire breadth of functionality concerning the identification and categorization of data. Labeling, monitoring, and enforcement each play important roles in a broader DLP framework but lack the comprehensive scope that "Discovery and Classification" encapsulates in the context of identifying and managing sensitive information.