Product recommendation systems handle new or unique products by using a mix of collaborative and content-based filtering techniques.
Collaborative filtering relies on user behavior, so if a new product hasn't been interacted with yet, collaborative filtering alone may not recommend it.
In such cases, content-based filtering comes into play. It examines the attributes of the new product and compares them to existing items.
This allows the system to recommend the new product to users who have shown interest in similar products or categories.