Explanation

Unsupervised Learning (Clustering) is the correct choice because:

• No pre-labeled data: The problem states "without having topic labels," which means there are no predefined categories or labels for the news articles
• Grouping similar items: Clustering algorithms automatically discover patterns and group similar documents together based on their content
• Topic discovery: This approach identifies natural groupings in the data, which can reveal topics that weren't predefined

Why other options are incorrect:

• A) Supervised Learning: Requires labeled training data with known topic categories
• B) Reinforcement Learning: Focuses on decision-making through trial and error with rewards/penalties, not document grouping
• D) Transfer Learning: Involves applying knowledge from one domain to another, but still typically requires some labeled data

Clustering algorithms like K-means, hierarchical clustering, or topic modeling techniques (LDA) are specifically designed for this type of unsupervised grouping task.