The important distinction here is between cache misses caused by the size of your data set, and cache misses caused by the way your cache and data alignment are organized.
Lets assume you have a 32k direct mapped cache, and consider the following 2 cases:
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You repeatedly iterate over a 128k array. There’s no way the data can fit in that cache, therefore all the misses are capacity ones (except the first access of each line which is a compulsory miss, and would remain even if you could increase your cache infinitely).
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You have 2 small 8k arrays, but unfortunately they are both aligned and map to the same sets. This means that while they could theoretically fit in the cache (if you fix your alignment), they will not utilize the full cache size and instead compete for the same group of sets and thrash each other. These are conflict misses, since the data could fit, but still collides due to organization. The same problem can occur with set associative caches, although less often (let’s say the cache is 2-way, but you have 4 aligned data sets…).
The 2 types are indeed related, you could say that given high levels of associativity, set skewing, proper data alignments and other techniques, you could reduce the conflicts, until you’re mostly left with true capacity misses that are unavoidable.