I'm struggling to understand the meaning of the term associative memory in the context of Hopfield networks. I'm not sure if associative learning is the same thing or a different thing. In associative learning, you have two unrelated items and you learn to associate one item with the other. In a hopfield network you have a partial pattern then you can retrieve the full pattern. How is this associative learning? Or are associative learning and associative memory different things?
An Associative Memory is a synonym for Content Addressable Memory or a memory which stores the result of associative learning, wherein an input item is learned to be associated with an output item.
A Hopfield network is a type of associative memory, wherein an input item (including partial, noisy representations of the original trained/encoded item) is an associated to a the ideal representation of the trained/desired/encoded input item.
For further discussion of Hopfield networks, I recommend look at the question "What's the difference between a Hamming and Hopfield network?"