Web of Science advanced search returns papers not matching the search criteria
Right, so there are three elements here (let's call them #1, energy, #2, plants, #3, animals)

TS=(Digestibility OR “energy content” OR “Nutritive value” OR “forage quality” OR “nutritional value“ OR “energy intake”)
AND
TS=(flower* OR leaf OR leaves OR litter OR branch OR branches OR twigs OR stem OR stems OR seeds OR seed OR fruit OR fruits)
AND
TS=(“herbivor*” OR “ungulate*” OR “mammals” OR “grazer*” OR “browser*” OR &quot;mix-feeder*” OR “livestock” OR “domestic animals” OR “captive animals”)

With no filters, in WoS Core Collection, I get 107k results for #1, 3023k results for #2, 270k results for #3. (Yours may differ depending on exactly which bits of the Core Collection your institution subscribes to).
Combined - #1 AND #2 AND #3 - I only get 1245, which is much more reasonable. But not the same as you were getting - why? You mentioned in the comments that you were searching All Databases rather than Core Collection.
Trying again in All Databases, I get 265k results for #1, 8490k for #2, 19019k(!!) for #3. And combined, 22532 results. So, we can see the problem here is driven by using All Databases. But why?
Normally, when you search a single database like Core Collection, you are only searching the Core Collection metadata for each article. This is not always as useful as you will find in other databases - eg MEDLINE might have really rich and detailed subject headings, but Core Collection will just have a few keywords.
An &quot;all databases&quot; search will search the metadata in all of them - MEDLINE, BIOSIS, Core Collection, and so on. It thus leverages metadata that only exists in one database even if the paper is found in several different ones - which can be really powerful, or can be really treacherous.
In this case, it's treacherous. You'll note that we get 2.5x as many for &quot;energy&quot;, 2.5x as many for &quot;plants&quot;, but 70x as many for &quot;animals&quot;. So what's up with &quot;animals&quot;?
Web of Science &quot;all databases&quot; includes BIOSIS (if you have a subscription to it). If you open up a paper's record in BIOSIS, you'll see that it includes extensive keyword/subject heading data. This is from the first paper I picked out which matches the &quot;animal&quot; part of your query - it's about congestion charging in China.

Because BIOSIS is structured in a very logical taxonomic way, this paper - and millions like it - will be returned by any search for animals, primates, vertebrates, mammals, etc. And your search includes the keyword &quot;mammals&quot;. Bingo. That keyword is massively inflating the results for your third section, and as a result a lot of papers that match parts #1 and #2 but you would not expect to match #3 are showing up as valid matches for all sections.
Drop out &quot;mammals&quot; and we go down to 473k results for that part in all databases, final results 3395 - much more reasonable and in line with the other results. The Core Collection search gives us 145k results for the animals search without &quot;mammals&quot;, 1139 overall.