Step 1 is getting a list of new products that are receiving a higher than expected number of 5-star reviews
Step 2, add it to a list of similar products.
Step 3, find accounts that all happen to purchase the same products in the same order.
Step 4, ban accounts and sellers.
What is higher than the expected number of 5-star reviews?
Don't those numbers vary widely depending on product category, brand, and newness of the product?
How does that work for things that fit into more than 1 product category?
That's left as an exercise for the reader ;)
But you could simplify this to new products, which if ungamed, would probably follow a predictable curve of discovery, as opposed to a games "instant 5 star" rating.
As Machine Learning is just a fancy way of doing statistics, you will totally not need it for this.