Sāmānyatodṛṣṭa anumāna involves inference based on general patterns of co occurrence rather than a clear temporal order of cause and effect. Movement of leaves is regularly associated with the presence of air or wind, even though air itself may not be directly perceived. From this generally observed relation, one infers air from leaf movement. Nyāya uses such examples to illustrate inference to entities known only through their effects.
Option A:
Option A, pūrvavat, describes inference from present cause to future effect, as when dark clouds lead us to expect rain.
Option B:
Option B, śeṣavat, is often used for inferring an unperceived cause from a known effect in a more definite causal chain, as in inferring fire from smoke.
Option C:
Option C correctly classifies the case as sāmānyatodṛṣṭa, where broad, repeated association lets us infer something unseen like air from an observable sign.
Option D:
Option D, kevalānvayi, refers to inference where only positive instances exist and no genuine negative instances are available, which is not the key feature of this example.
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